1

Google Cloud Machine Learning Engineer Jobs in Atlanta, GA

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

As a Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast ... Experience working in a cloud environment such as AWS, Google Cloud Platform, Azure. * Experience ...

Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform (GCP) using ... Ph.D. preferred. * 5+ years of professional experience in machine learning engineering, with a ...

Senior Machine Learning Engineer I

Atlanta, GA · On-site

$117K - $155K/yr

Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform (GCP) using ... Ph.D. preferred. * 5+ years of professional experience in machine learning engineering, with a ...

Machine Learning Engineer

Atlanta, GA · On-site

$125 - $150/hr

Job Summary We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team at Speria MTech. The ideal candidate will play a crucial role in designing, building, and ...

Senior ML Engineer

Atlanta, GA · On-site

$125 - $150/hr

... and innovative Machine Learning Engineer to develop end‑to‑end ML pipelines, fine‑tune language models, design agentic architectures, and deploy solutions on Google Cloud Platform.

AI Engineer

Alpharetta, GA · On-site

$125 - $150/hr

... machine learning lifecycle management, with strong proficiency in Python, SQL, and Google Cloud ... Python Programming * SQL Database Querying * Google Cloud Platform (GCP) * Apache Airflow Hard ...

New

Cyber - Google Cloud Security - Manager

Atlanta, GA · On-site

$106K - $144K/yr

... machine learning security, container security, data protection, monitoring, and secure delivery ... Serving as the primary day-to-day client contact, driving outcomes across engineering, security ...

Cyber - Google Cloud Security - Manager

Atlanta, GA · On-site

$106K - $144K/yr

... machine learning security, container security, data protection, monitoring, and secure delivery ... Serving as the primary day-to-day client contact, driving outcomes across engineering, security ...

Showing results 21-40

Google Cloud Machine Learning Engineer information

See Atlanta, GA salary details

$22

$60

$83

How much do google cloud machine learning engineer jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for google cloud machine learning engineer in Atlanta, GA is $60.47, according to ZipRecruiter salary data. Most workers in this role earn between $51.54 and $68.89 per hour, depending on experience, location, and employer.

What is a Google Cloud Machine Learning engineer?

Google Cloud Machine Learning Engineers are professionals who design, build, and deploy machine learning models using Google Cloud Platform (GCP) services and tools. They work with large datasets, develop scalable ML solutions, and collaborate with data scientists and software engineers. Their role often includes automating data pipelines, optimizing model performance, and ensuring the reliability and security of ML deployments on the cloud. These engineers have expertise in both machine learning algorithms and cloud infrastructure, making them key contributors to data-driven projects.

What are the key skills and qualifications needed to thrive as a Google Cloud Machine Learning engineer?

To thrive as a Google Cloud Machine Learning Engineer, you need strong programming skills in Python or Java, a deep understanding of machine learning algorithms, and a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, TensorFlow, and relevant certifications like the Professional Machine Learning Engineer certification is highly valuable. Excellent problem-solving abilities, collaboration, and clear communication make someone stand out in this position. These skills and qualities are critical for designing, deploying, and optimizing scalable ML solutions that meet business objectives in cloud environments.

What are some typical cross-functional collaborations for a Google Cloud Machine Learning engineer?

As a Google Cloud Machine Learning Engineer, you'll frequently work alongside data scientists, software engineers, and product managers to design, deploy, and maintain machine learning solutions at scale. Collaboration often involves translating business requirements into machine learning pipelines, integrating models into cloud-based applications, and ensuring that solutions are robust, secure, and scalable. Regular communication with DevOps and infrastructure teams is also common to optimize model deployment and monitor performance. This cross-disciplinary teamwork is crucial for delivering impactful, production-ready AI solutions.

What is the difference between Google Cloud Machine Learning Engineer vs Data Scientist?

AspectGoogle Cloud Machine Learning EngineerData Scientist
Required CredentialsGoogle Cloud certifications, programming skills, ML knowledgeStatistics, data analysis, programming, often with advanced degrees
Work EnvironmentCloud platforms, coding, deploying ML modelsData analysis, modeling, reporting, often in research or business settings
Employer & Industry UsageTech companies, cloud service providers, enterprises using Google CloudVarious industries including finance, healthcare, marketing, research

Google Cloud Machine Learning Engineers focus on developing and deploying ML models on Google Cloud, requiring cloud certifications and coding skills. Data Scientists analyze data, build models, and generate insights, often with advanced degrees. While both roles work with data and ML, the Engineer role emphasizes cloud deployment and infrastructure, whereas Data Scientists focus on data analysis and modeling.

What are the most commonly searched types of Google Cloud Machine Learning Engineer jobs in Atlanta, GA?

The most popular types of Google Cloud Machine Learning Engineer jobs in Atlanta, GA are:

What job categories do people searching Google Cloud Machine Learning Engineer jobs in Atlanta, GA look for?

The top searched job categories for Google Cloud Machine Learning Engineer jobs in Atlanta, GA are:

What cities near Atlanta, GA are hiring for Google Cloud Machine Learning Engineer jobs?

Cities near Atlanta, GA with the most Google Cloud Machine Learning Engineer job openings:

Machine Learning Engineer (MLE) - Q123

Alpharetta, GA • On-site

Full-time

Medical, Dental, Vision, PTO

Re-posted 11 days ago


Job description

Overview:
R2 Technologies Corporation (R2) is a technology services provider headquartered in Alpharetta, GA, with expertise in a range of cutting-edge technologies. R2 specializes in Java, Dot Net, Big Data, Cloud Computing, artificial intelligence (AI), machine learning (ML), software development, project management, SAP, and enterprise resource planning (ERP) systems. Additionally, R2 offers highly skilled resources and productivity platforms that enable clients to rapidly deliver business value to their stakeholders.
R2's strength lies in providing platform-based solutions, architecting, and designing enterprise solutions, leveraging cloud technologies such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure to deliver scalable and cost-effective solutions.
R2's expertise in AI and ML enables clients to leverage the power of data to make data-driven decisions and improve their overall performance. R2 also provides solutions for internet of things (IoT) and blockchain technologies, which can help clients improve their supply chain management and streamline their operations.
Since its inception, R2 has rapidly grown to become one of the most respected and trusted technology companies in the United States, providing product development and staffing services to a diverse range of clients, including small and midsize businesses, as well as Fortune 1000 companies.
Job Title: Machine Learning Engineer (MLE)
Location: Alpharetta, GA.
Type: Full-time
Overview:
We are seeking a skilled and experienced Developer to join our team. The ideal candidate will have expertise in programming and experience in building scalable and reliable applications.
Responsibilities:
• The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:
• Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
• Use programming languages like Python, Scala, or Java.
• API development
Required Skills:
• At least 3 years of experience programming with Python, Scala, or Java (Internship experience does not apply)
• At least 3 years of experience designing and building data-intensive solutions using distributed computing
• At least 3 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)
• At least 1 year of experience productionizing, monitoring, and maintaining models
Optional Skills:
• 3 years of experience building, scaling, and optimizing ML systems
• 3 years of experience with data gathering and preparation for ML models
• 3 years of experience developing performant, resilient, and maintainable code
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• 3 years of experience with distributed file systems or multi-node database paradigms
• 3 years of experience building production-ready data pipelines that feed ML models
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
Qualifications:
• Bachelor's degree in computer science, Engineering, or related field.
• Relevant certification.
Attributes:
We are seeking a candidate who is passionate, intelligent, and a critical thinker. The ideal candidate should be a proactive communicator, documenting their work clearly and succinctly. They should be detail-oriented, thoughtful, and respectful, with a focus on teamwork. The candidate should possess strong problem-solving skills and have the ability to work independently and within a team. They should be able to adapt to changing requirements and maintain a positive attitude in a fast-paced environment.
What's In It for You?
We offer competitive benefits, pay, and bonus potential, including group health insurance, vision and dental insurance, and paid vacation.
Skills:
Machine Learning,Artificial Intelligence,Python